Job Title: Data Analyst

Role Summary

The Data Analyst plays a critical role in safeguarding the accuracy, integrity, and reliability of large and complex datasets. This role focuses on developing scalable dataquality capabilities and automated validation frameworks and intelligent anomaly detection without requiring domain knowledge of the underlying business data.

You will collaborate closely with data engineering, product, and reporting teams, ensuring that data feeding our operational, analytical, and AIdriven systems is trustworthy, consistent, and ready for decisionmaking. The ideal candidate combines technical depth with strong analytical intuition and thrives in dataintensive, fastmoving environments.

Key Responsibilities

Data Quality & Validation

• Perform in depth validation of structured and unstructured datasets to ensure completeness, consistency, accuracy and lineage integrity.
• Apply statistical techniques, pattern recognition methods, and anomaly detection algorithms to identify irregularities without requiring domain-expertise.
• Design and implement automated datavalidation checks, including schema validation, threshold monitoring, drift and distribution detection, and rulesbased and machine learning based assessments.

Tooling & Automation

• Develop scripts, tools, and data pipelines to automate data-quality assessments.
• Build reusable frameworks to detect data inconsistencies across multiple sources and formats.
• Integrate validation tools into existing data infrastructure (e.g., ETL/ELT pipelines, data warehouses, APIs and event driven architectures).

Required Skills & Qualifications

Technical Skills

• Strong proficiency in SQL (data extraction, cleaning, and validation).
• Experience with Python or R for data processing, automation, and tool development.
• Familiarity with dataquality frameworks, anomaly detection techniques, and statistical validation.
• Experience working with large datasets and modern dataplatform technologies.
• Knowledge of dataintegration patterns (ETL/ELT) and monitoring tools.
• Familiar with GenAI concepts and prompt engineering and LLM assisted automation
• Experienced in building agents with MS Copilot studio or comparable technology

Analytical Skills

• Excellent problemsolving skills especially in contexts where domain knowledge is limited.
• Ability to identify trends, irregularities, and outliers using structured and unstructured methods.
• Strong logical reasoning, abstraction and hypothesis driven thinking
• Demonstrate patternrecognition abilities, translating data signals into actionable insights.

Preferred Qualifications

• Experience with dataquality monitoring tools (i.e. SODA).
• Familiar with data engineering concepts